Large scale tensor regression using kernels and variational inference.
Robert HuGeoff K. NichollsDino SejdinovicPublished in: Mach. Learn. (2022)
Keyphrases
- variational inference
- gaussian process
- gaussian processes
- bayesian inference
- topic models
- regression model
- probabilistic graphical models
- support vector
- probabilistic model
- latent dirichlet allocation
- mixture model
- posterior distribution
- variational methods
- model selection
- closed form
- exponential family
- higher order
- hyperparameters
- feature space
- exact inference
- approximate inference
- kernel methods
- kernel function
- generative model
- graphical models
- bayesian framework
- prior information
- markov networks
- multiple kernel learning
- expectation maximization
- parameter estimation
- image sequences